CN111950176B - Optimization method and optimization device for billet heating model and electronic equipment - Google Patents
Optimization method and optimization device for billet heating model and electronic equipment Download PDFInfo
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Abstract
The invention discloses an optimization method of a billet heating model, which comprises the following steps: performing combustion calculation, and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; performing heat transfer calculation according to the sectional furnace temperature, and determining the steel billet finishing temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conductivity lambda j and the steel billet heating time t; performing billet heating temperature field simulation by adopting a finite difference iteration method to obtain a billet heating calculation model; heating the steel billet according to the steel billet heating calculation model to obtain actual temperature rise data of the steel billet; correcting the billet heating calculation model according to the billet heating calculation model and actual heating data; the optimization method integrates the combustion, heat transfer, billet temperature field simulation and heating model correction processes, and realizes effective control of billet heating temperature and quality.
Description
Technical Field
The application relates to the technical field of steel hot rolling, in particular to an optimization method and an optimization device for a billet heating model and electronic equipment.
Background
With the improvement of the quality requirements of steel products, the surface quality requirements of steel are higher and higher, the requirements on rolling the steel are also tighter and the heating of billets is more and more important. Although continuous casting and rolling technology is rapidly developed, temperature drop and heat loss in the continuous casting process are unavoidable, so that the heating of the slab is an important link of the added steel in the hot rolling production process. The billet heating is a complex physicochemical process, and the low-cost and high-efficiency steel rolling can be realized by mastering the heating rule.
The billet is heated in the furnace to be unsteady heat conduction, and a heating mathematical model is established for the heating process of the billet in the heating furnace and is used for guiding the process control of the billet heating furnace. However, the billet heating model obtained by the existing heating model determining method has larger deviation from the actual temperature rising process of the billet, and practical production cannot be directly guided. For this reason, the determination process of the heating model needs to be optimized to obtain a heating model with higher accuracy and better matching with the actual heating temperature increasing process.
Disclosure of Invention
The invention provides an optimization method, an optimization device and electronic equipment for a billet heating model, and aims to solve or partially solve the technical problem that the billet heating model determined by the existing method has larger deviation from the actual heating process.
In order to solve the technical problems, the invention provides an optimization method of a billet heating model, which comprises the following steps:
Acquiring initial parameters of combustion calculation, performing the combustion calculation, and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
Acquiring initial parameters of heat transfer calculation, performing heat transfer calculation according to the sectional furnace temperature, and determining the steel billet finishing temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conductivity coefficient lambda j and the steel billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging amount and heating furnace size information;
According to the billet charging temperature T 0, the billet finishing temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conductivity coefficient lambda j and the billet heating time T, performing billet heating temperature field simulation by adopting a finite difference iteration method to obtain a billet heating calculation model;
Heating the steel billet according to the steel billet heating calculation model to obtain actual temperature rising data of the steel billet in the heating process;
and correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual temperature rise data to obtain a target calculation heating model.
Optionally, determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace specifically comprises:
determining the combustion load according to the volume flow of the gas and the low-position heating value of the gas;
Determining the temperature of the flue gas according to the volume flow of the gas, the low-level heating value of the gas, the preheating temperature of the gas, the specific heat of the gas, the air-fuel ratio, the specific heat of air, the preheating temperature of the air and the volume flow of the air;
And determining the flue gas flow according to the theoretical flue gas amount, the theoretical dry air amount and the air coefficient.
Optionally, the gas components include CO, CO 2、N2, and H 2; the preheating temperature of the gas is 200-300 ℃ and the preheating temperature of the air is 450-550 ℃.
Optionally, determining the billet end temperature Tz, the billet specific heat segment C pj, the billet segment heat conductivity coefficient lambda j and the billet heating time t specifically comprises:
determining the heat absorption quantity Q of the steel billet according to the sectional furnace temperature and the steel billet loading quantity;
Determining the billet finishing temperature Tz according to the billet heat absorption Q, the billet charging temperature T 0 and the billet charging specific heat C p0;
determining a billet sectional specific heat C pj according to the billet finishing temperature Tz and the billet charging specific heat C p0;
Determining a billet sectional heat conduction coefficient lambda j according to the billet finishing temperature Tz and the billet charging heat conduction coefficient lambda 0;
And determining the billet heating time t according to the billet finishing temperature Tz, the billet sectional specific heat C pj and the billet sectional heat conductivity lambda j.
Optionally, the sectional furnace temperature includes: the furnace temperature of the first heating section is 800-1100 ℃, the furnace temperature of the second heating section is 1100-1150 ℃, and the furnace temperature of the soaking section is 1150-1250 ℃.
Optionally, performing a billet heating temperature field simulation by using a finite difference iteration method to obtain a billet heating calculation model, which specifically includes:
determining a thickness step delta x according to the thickness h of the steel billet, determining a time step delta tau according to the heating time t, and constructing a calculation grid of thickness nodes-time steps;
Taking the steel billet charging temperature T 0 as an initial value, and carrying out finite difference iteration on a calculation grid according to the steel billet sectional specific heat C pj and the steel billet sectional heat conductivity coefficient lambda j to obtain node calculation temperature of all thickness nodes on the calculation grid, wherein the node calculation temperature changes along with the time step delta tau Calculating temperature from nodesObtaining a calculated heating model; wherein i is more than or equal to 1 and less than or equal to h/delta x and is a positive integer, and n is more than or equal to 1 and less than or equal to t/delta tau and is a positive integer.
Further, with the billet charging temperature T 0 as an initial value, performing finite difference iteration on a calculation grid according to the billet sectional specific heat C pj and the billet sectional heat conductivity coefficient lambda j, and specifically including:
A linear equation set is established according to the following finite difference equation, the temperature T 0 of the billet entering into the furnace is used as the initial value of each thickness node, and the temperature is calculated for the node Performing finite difference iteration:
Wherein ρ g is the billet density.
Further, according to the temperature deviation between the billet heating calculation model and the actual temperature rising data, correcting the billet heating calculation model to obtain a target calculation heating model, specifically comprising:
Judging whether the absolute value of the temperature deviation between the billet calculation final temperature in the billet heating calculation model and the billet actual final temperature in the actual temperature rise data is within 5 ℃;
If yes, determining the billet heating calculation model as a target calculation heating model;
If not, calculating the temperature from the node Node calculation temperature/>, corresponding to node k of target thickness
Determining node heating data corresponding to the target thickness node k and the time step delta tau from the actual heating data
Calculating temperature for nodeAnd node warming data/>Performing mean value processing to obtain target node temperature/>, of target thickness node kThe target node temperature/>And (5) performing polynomial fitting to obtain a target heating model.
Based on the same inventive concept as the technical scheme, the invention also provides an optimizing device of the billet heating model, which comprises:
The combustion calculation module is used for acquiring initial parameters of combustion calculation, performing the combustion calculation and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
The heat transfer calculation module is used for acquiring initial parameters of heat transfer calculation, performing heat transfer calculation according to the sectional furnace temperature, and determining the billet finishing temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conductivity coefficient lambda j and the billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging amount and heating furnace size information;
The temperature field simulation module is used for performing steel billet heating temperature field simulation by adopting a finite difference iteration method according to the steel billet charging temperature T 0, the steel billet finishing temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conduction coefficient lambda j and the steel billet heating time T to obtain a steel billet heating calculation model;
the acquisition module is used for heating the steel billet according to the steel billet heating calculation model and acquiring actual temperature rising data of the steel billet in the heating process;
and the correction module is used for correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual temperature rise data to obtain the target calculation heating model.
Based on the same inventive concept as the above technical scheme, the invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the optimization method in the above technical scheme when executing the program.
Through one or more technical schemes of the invention, the invention has the following beneficial effects or advantages:
The invention discloses an optimization method of a billet heating model, which is characterized in that a segmentation input parameter required by heating model calculation more in line with the actual working condition of a billet and the actual working condition of a heating furnace is obtained by adopting a de-novo calculation mode of combustion calculation and heat transfer calculation, then a calculation heating model is obtained by adopting a finite difference iteration method, and the billet heating is controlled by using the calculation heating model to obtain the actual heating data of the billet; and correcting the heating model according to the temperature deviation between the actual heating data and the calculated heating model. The combustion, heat transfer and billet temperature field simulation are integrated with the heating model correction process through the de-header calculation of billet heating, so that the calculation accuracy of the billet heating model is improved, the iteration speed of the billet heating model is accelerated, the correction times of the heating model are reduced, the effective control of the billet heating temperature and quality is realized, and the heating control cost is reduced.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 shows a flowchart of a method for optimizing a billet heating model according to one embodiment of the present invention;
FIG. 2 illustrates a schematic diagram of modifying a billet heating calculation model according to one embodiment of the invention;
FIG. 3 shows an overall furnace apparatus arrangement of FIG. 1 according to one embodiment of the invention;
FIG. 4 shows an overall furnace apparatus arrangement of FIG. 2 according to one embodiment of the invention;
FIG. 5 is a process diagram showing an implementation of an optimization method of an X80 billet heating model according to one embodiment of the invention;
Reference numerals illustrate:
1. Pulse heating device 2, soaking zone left first air valve group, 3, soaking zone left first gas valve group, 4, soaking zone left second air valve group, 5, soaking zone left second gas valve group, 6, two heating zone left first air valve group, 7, two heating zone left first gas valve group, 8, two heating zone left second air valve group, 9, two heating zone left second gas valve group, 10, one heating zone left first air valve group, 11, one heating zone left first gas valve group, 12, one heating zone left second air valve group, 13, one heating zone left second gas valve group, 14, soaking zone left first air nozzle group, 15, soaking zone left first gas nozzle group, 16, soaking zone left second air nozzle group, 17, soaking zone left second gas nozzle group, 18, soaking zone left partition wall, 19, two heating zone left first air nozzle group, 20, 21, 22, 23, 33, 34, 35, 36, and 34, 37. a second gas jet group on the right side of the two heating sections, 38, a partition wall on the right side of the two heating sections, 39, a first gas jet group on the right side of the heating sections, 40, a first gas jet group on the right side of the heating sections, 41, a second gas jet group on the right side of the heating sections, 42, a second gas jet group on the right side of the heating sections, 43, a partition wall on the right side of the heating sections, 44, a first air valve group on the right side of the soaking sections, 45, a first gas valve group on the right side of the soaking sections, 46, a second air valve group on the right side of the soaking sections, 47, a second gas valve group on the right side of the soaking sections, 48, a first air valve group on the right side of the two heating sections, 49, a first gas valve bank on the right side of the two heating sections, 50, a second air valve bank on the right side of the two heating sections, 51, a second gas valve bank on the right side of the two heating sections, 52, a first air valve bank on the right side of the one heating section, 53, a first gas valve bank on the right side of the one heating section, 54, a second air valve bank on the right side of the one heating section, 55, a second gas valve bank on the right side of the one heating section, 56, an air main valve, 57, an air main pipe, 58, an air main valve, 59, a gas main pipe, 60, a chimney, 61, a first flue valve, 62, a gas heat exchanger, 63, a billet, 64, a second flue valve, 65, an air heat exchanger, 66 and a third flue valve.
Detailed Description
In order to make the present application more clearly understood by those skilled in the art, the following detailed description of the technical scheme of the present application will be given by way of specific examples with reference to the accompanying drawings. Throughout the specification, unless specifically indicated otherwise, the terms used herein should be understood as meaning as commonly used in the art. Accordingly, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. In case of conflict, the present specification will control. The various devices and the like used in the present application are commercially available or can be prepared by existing methods unless otherwise specifically indicated.
Research shows that the existing heating model determining method mainly focuses on improvement or optimization of a heating model determining algorithm, and for input parameters used for heating model calculation, existing data provided by existing documents and tool books, such as billet specific heat, billet heat transfer coefficient and the like, are directly used as input, and a heating model is established through a finite element method, a finite volume method and the like. The problem of the method at present is that the influence of the actual working condition of the heating furnace, the billet charging information and the change of the billet specification on the input parameters of the heating model is not considered; because the existing heating model determining method does not take the accuracy of calculation parameters into consideration in the global aspect of the heating process, the low-accuracy heating model input parameters directly influence the calculation accuracy of the subsequent heating models, so that larger deviation exists between the calculated heating model and the actual heating data of the billet which is produced according to the heating model guidance, and the heating model needs to be corrected for multiple times according to the actual heating data, so that the corrected heating model and the actual heating data can be coupled. Multiple heating model modification processes will result in a significant increase in the production costs of the heating section.
Based on the above-mentioned research results, in an alternative embodiment, as shown in fig. 1, there is provided a method for optimizing a billet heating model, including:
S1: acquiring initial parameters of combustion calculation, performing the combustion calculation, and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
According to the heating model optimization method provided by the embodiment, from the initial combustion calculation, the actual gas parameters, the air parameters and the pulse burner parameters are considered to calculate the combustion load, the flue gas temperature and the flue gas flow, so that the result of the combustion calculation of the heating furnace fuel and the actual working condition of the heating furnace burner is combined as the input of the billet heat transfer calculation, and the accuracy of the billet heat transfer calculation can be improved.
Optionally, the method for determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace comprises the following steps:
Firstly, determining the low-level heating value of the gas according to the gas components;
Namely, the low heat productivity of the gas
Wherein:
CO and H 2、CH4、C2H6、H2 S, the volume content of each gas component.
Then, determining the gas volume flow V g according to the working pulse burner load and the number of the pulse burners;
Wherein: m-the number of pulse burner groups operated; n i -number of pulse burners of the i-th group operated; the i-th group pulse burner load P i is operated.
Then, determining the combustion load according to the low-level heating value of the gas and the volume flow of the gas;
namely, the combustion load Q r is
Then, the actual flue gas flow is determined according to the theoretical flue gas amount, the theoretical dry air amount and the air coefficient.
Namely, the actual flue gas flow is:
Wherein: v 0 -theoretical smoke volume;
Alpha-air coefficient;
g k -air moisture content;
-theoretical dry air quantity.
Then, determining the flue gas temperature according to the volume flow of the gas, the low-level heating value of the gas, the preheating temperature of the gas, the specific heat of the gas, the air-fuel ratio, the specific heat of air, the preheating temperature of the air and the volume flow of the air;
Namely: the flue gas temperature is:
Wherein: t f -flue gas temperature;
V g -gas volume flow;
c g -specific heat of gas;
t g -gas preheating temperature;
R-air-fuel ratio;
C α -specific heat of air;
t α -air preheating temperature;
C f -specific heat of flue gas;
v f -volumetric flow of flue gas.
Compared with the traditional calculation method, the production data tracking shows that the flue gas temperature calculated by combining the actual gas working condition parameter, the air working condition parameter and the flue gas working condition parameter of the heating furnace is more accurate.
After the combustion load, the flue gas temperature and the flue gas flow are obtained, the sectional furnace temperature of the heating furnace can be determined according to the furnace temperature calculation model. The sectional furnace temperature of the heating furnace comprises a preheating section furnace temperature, a first heating section furnace temperature, a second heating section furnace temperature, a third heating section furnace temperature and a soaking section furnace temperature.
Optionally, the gas used in the heating furnace in this embodiment is mixed gas, and the gas components include CO, CO 2、N2, and H 2; the preheating temperature of the gas is 200-300 ℃ and the preheating temperature of the air is 450-550 ℃.
Optionally, pulse burners of the first heating section, the second heating section and the soaking section of the heating furnace are adjusted in a decentralized control manner, and the proportion of the number of the two states of opening or closing of the pulse burners is increased or decreased during load adjustment
According to the working condition parameters and the gas parameters of the heating furnace, the calculated sectional furnace temperature comprises: the furnace temperature of the first heating section is 800-1100 ℃, the furnace temperature of the second heating section is 1100-1150 ℃, and the furnace temperature of the soaking section is 1150-1250 ℃.
After the combustion calculation is completed, the heat transfer calculation can be performed, specifically as follows:
S2: acquiring initial parameters of heat transfer calculation, performing heat transfer calculation according to the sectional furnace temperature, and determining the steel billet finishing temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conductivity coefficient lambda j and the steel billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging yield and heating furnace size information;
Specifically, the billet density is determined by the billet composition;
ρg＝f(C,Si,Mn)；
C, si, mn-is the percentage of the billet components;
The single weight of the steel billet is determined by the size and the density of the steel billet;
Gg＝ρg*L*W*H；
L, W and H-are respectively the length, width and height of the steel billet;
determining the sectional heat absorption quantity Q j of the steel billet according to the sectional furnace temperature and the steel billet loading yield;
Qj＝f(Tlj,Gz)；
T lj -j-th section furnace temperature, gz-billet charging yield;
Determining the steel billet finishing temperature Tz according to the total heat absorption quantity Q of the steel billet, the steel billet charging temperature T 0 and the steel billet charging specific heat C p0;
The calculation equation of the billet finishing temperature Tz is as follows:
Tz＝(Q+Cp0*Tp0)/Cpg；
Wherein C pg is the final specific heat of the steel billet, and is the final specific heat of the steel billet obtained by inquiring from the tool book at the target tapping temperature according to the preset target tapping temperature of the steel billet;
Determining the billet sectional specific heat C pj according to the j-th section furnace temperature T lj, the billet finishing temperature Tz and the billet charging specific heat C p0;
specifically, C pj＝f(Cp0,Tlj,Tz);
Determining a billet sectional heat conduction coefficient lambda j according to the billet finishing temperature Tz and the billet charging heat conduction coefficient lambda 0;
specifically, λ j＝f(λ0,Tlj,Tz);
And determining the billet heating time t according to the billet finishing temperature Tz, the billet sectional specific heat C pj and the billet sectional heat conductivity lambda j.
Wherein the heating time t comprises a segment heating time t j, the sum of the segment heating time t j is the total heating time t, and the algorithm of t j is as follows:
tj＝f(Tz,Cpj,λj)；
The sectional parameters such as the sectional specific heat, the sectional heat conductivity coefficient and the like comprise a preheating section, a first heating section, a second heating section, a third heating section and a soaking section of the heating furnace.
S3: according to the billet charging temperature T 0, the billet finishing temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conductivity coefficient lambda j and the billet heating time T, performing billet heating temperature field simulation by adopting a finite difference iteration method to obtain a billet heating calculation model;
Alternatively, the finite difference iteration process is as follows:
S31: determining a thickness step delta x according to the thickness h of the steel billet, determining a time step delta tau according to the heating time t, and constructing a calculation grid of thickness nodes-time steps;
The method comprises the steps of discretizing a solving domain of billet heating temperature, dividing a space and time region involved in the heating process of a heating furnace into limited sub-regions according to square grids, wherein each node temperature represents the temperature of the sub-region in a certain time. The space scale is the thickness of the steel billet, and the time scale is the heating time of the steel billet in the heating furnace. In order to ensure the calculation accuracy without obviously increasing the calculation workload, dividing the thickness of the billet into 50-100 nodes; the thickness of the steel billet is generally 200-500 mm, so the value range of the thickness step delta x is 0.2-10 mm; then the heating time step is divided according to 1-2 min.
After node grids are divided, finite difference can be carried out, a finite difference equation set of node temperature is established, and temperature values of all nodes are obtained by solving the finite difference equation set, and the method specifically comprises the following steps:
S32: taking the steel billet charging temperature T 0 as an initial value, and carrying out finite difference iteration on a calculation grid according to the steel billet sectional specific heat C pj and the steel billet sectional heat conductivity coefficient lambda j to obtain node calculation temperature of all thickness nodes on the calculation grid, wherein the node calculation temperature changes along with the time step delta tau Calculating temperature from nodesObtaining a calculated heating model; wherein i is more than or equal to 1 and less than or equal to h/delta x and is a positive integer, and n is more than or equal to 1 and less than or equal to t/delta tau and is a positive integer.
In this embodiment, a second-order difference is adopted for the rate of change of the temperature of the node i with respect to time, and the obtained finite difference iteration equation is:
Wherein ρ g is the billet density.
According to the finite difference equation, a linear equation set is established for all thickness nodes to carry out iterative solution. Firstly, the initial value of the node temperature of the billet is setThe billet entering temperature T 0 is brought into an equation set, then the temperature value of the next time node is obtained, and the temperature value is used as the input of the equation set to continue iteration; in the calculation process, the values of the billet sectional specific heat C pj and the billet sectional heat conductivity coefficient lambda j are confirmed according to the sectional furnace temperature to which the calculated temperature of the current node belongs; by repeated iteration of the process, the node calculation temperature value/>, under different time nodes n, of each thickness node i can be solvedFinally, node calculation temperature sets/>, of all thickness nodes in the whole heating time t, are obtainedThis is the required computational heating model.
Optionally, when performing finite difference iteration, determining that the iteration converges to stop continuing the iteration has a convergence criterion of: When the temperature value deviation after two iterations is smaller than 10 -3 ℃, the steel billet is fully soaked in the heating furnace, and then tapping is carried out.
S4: heating the steel billet according to the steel billet heating calculation model to obtain actual temperature rising data of the steel billet in the heating process;
After the heating calculation model is obtained, the heating of the steel billet can be automatically controlled in the heating furnace control system according to the heating calculation model, and in the heating process, the control system automatically acquires actual temperature rising data (curve) of the steel billet.
S5: and correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual temperature rise data to obtain a target calculation heating model.
Optionally, S5 specifically includes:
s51: judging whether the absolute value of the temperature deviation between the billet calculation final temperature in the billet heating calculation model and the billet actual final temperature in the actual temperature rise data is within 5 ℃;
s51: if yes, determining the billet heating calculation model as a target calculation heating model;
S52: if not, calculating the temperature from the node Node calculated temperature corresponding to node k of determined target thickness
S53: determining node heating data corresponding to the target thickness node k and the time step delta tau from the actual heating data
S54: calculating temperature for nodeAnd node warming data/>Performing mean value processing to obtain target node temperature/>, of target thickness node kThe target node temperature/>And (5) performing polynomial fitting to obtain a target heating model.
In actual control, the node calculation temperature and node heating data of the thickness node with the position representative, such as the surface of a steel billet or the thickness node at the 1/2 position in the middle of the steel billet, can be extracted for correction, the calculated value and the actual value are averaged according to the time node to obtain a target value, and polynomial fitting is carried out on the target value to obtain a corrected target heating model. Studies have shown that the heating curve obtained by fitting with a polynomial of degree 3 has the smallest fitting error.
Specifically, as shown in fig. 2, a correction schematic of a heating model is illustrated by taking a 1/2 position node in the middle of a steel billet as an example: the line 71 is a 1/2 node calculation temperature curve in the heating calculation model, the line 72 is a heating curve at the 1/2 position of the middle part of the billet in actual measurement, and certain deviation exists between the two curves, so that the heating calculation model needs to be corrected; the method of correction is to average the node temperature values in the line 71 and the line 72, and then perform polynomial fitting on the average node temperature for three times to obtain a corrected heating calculation model 73.
According to the billet heating model optimizing method, the calculation and determination steps can be automatically realized through secondary development of the existing heating calculation model software.
The billet heating model optimization method provided by the embodiment has the following advantages:
(1) The obtained heating model has high precision, less correction times and better guide production actual effect;
According to the heating model optimization method, according to the actual information of the steel billet and the actual working condition of the heating furnace, a de-novo calculation mode of combustion calculation and heat transfer calculation is adopted to obtain segmented input parameters required by heating model calculation which more accords with the actual working conditions of the steel billet and the heating furnace; by integrating the combustion, heat transfer and billet temperature field simulation and correction processes, the calculation accuracy of the billet heating model is improved. According to the method provided by the embodiment, the absolute value of the final temperature of the heating model billet and the actual measured final temperature of the billet, which are obtained or corrected through finite difference iteration, is less than 5 ℃, so that the billet heating process requirement is met.
(2) Solving the temperature measurement problem of the steel billet and realizing the visualization of the overall temperature distribution of the steel billet;
the heat transfer of the internal temperature of the steel billet is invisible, the temperature measurement needs to be perforated, the number of the perforated holes is very limited, the number of measuring points can be greatly reduced by adopting model calculation, and the temperature field of the steel billet can be drawn by using model calculation temperature distribution data, so that the visualization is realized.
(3) The optimization process is simple and can be repeatedly used;
the temperature field is calculated by adopting simplified finite difference iteration, namely, the previous calculation result is used as an initial parameter to be substituted into equation calculation in a sequential loop, so that temperature data convergence can be realized quickly, and the mathematical calculation process has the characteristics of simplicity and repeatability.
(4) The applicability is wide;
The heating model has universality, is generally adopted in secondary control, can meet the heating requirements of products such as pipeline steel, automobile plates, silicon steel and the like, and has wide application range.
In general, the embodiment discloses an optimization method of a billet heating model, which obtains sectional input parameters required by heating model calculation more in line with actual billet working conditions and actual heating furnace working conditions by adopting a mode of de-novo calculation of combustion calculation and heat transfer calculation, then obtains a calculation heating model by adopting a finite difference iteration method, and controls billet heating by using the calculation heating model to obtain actual billet heating data; and correcting the heating model according to the temperature deviation between the actual heating data and the calculated heating model. The combustion, heat transfer and billet temperature field simulation are integrated with the heating model correction process through the de-header calculation of billet heating, so that the calculation precision of the billet heating model is improved, the iteration speed of the billet heating model is accelerated, the correction times of the heating model are reduced, the effective control of the billet heating temperature and quality is realized, and the heating control cost is reduced; the production tracking result shows that the temperature deviation between the calculated heating model obtained by the method and the actual heating data of the steel billet is not more than 5 ℃.
Based on the same inventive concept as the previous embodiments, in yet another alternative embodiment, there is provided an optimizing apparatus of a billet heating model, comprising:
The combustion calculation module is used for acquiring initial parameters of combustion calculation, performing the combustion calculation and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
The heat transfer calculation module is used for acquiring initial parameters of heat transfer calculation, performing heat transfer calculation according to the sectional furnace temperature, and determining the billet finishing temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conductivity coefficient lambda j and the billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging amount and heating furnace size information;
The temperature field simulation module is used for performing steel billet heating temperature field simulation by adopting a finite difference iteration method according to the steel billet charging temperature T 0, the steel billet finishing temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conduction coefficient lambda j and the steel billet heating time T to obtain a steel billet heating calculation model;
the acquisition module is used for heating the steel billet according to the steel billet heating calculation model and acquiring actual temperature rising data of the steel billet in the heating process;
and the correction module is used for correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual temperature rise data to obtain the target calculation heating model.
And programming and developing based on the optimization method provided by the embodiment to obtain optimization software of the billet heating model, and automatically executing calculation and correction of the heating model.
Based on the same inventive concept as the previous embodiments, in yet another alternative embodiment, there is also provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the optimization method in the previous embodiments when the processor executes the program.
In the following embodiment, the above-described optimization method will be described in detail using pipeline steel X80 as an example:
A billet heating furnace used in a certain steel mill is a pulse heating device, and the arrangement diagrams thereof are shown in fig. 3 to 4: the gas preheated by the gas heat exchanger 62 is divided into two paths by the gas main pipe 59, wherein one path is divided into three paths, the first gas enters the first gas jet group 15 on the left side of the soaking section and the second gas jet group 17 on the left side of the soaking section respectively by the first gas jet group 3 on the left side of the soaking section and the second gas jet group 5 on the left side of the soaking section, the second gas enters the first gas jet group 20 on the left side of the two heating sections and the second gas jet group 22 on the left side of the two heating sections respectively by the first gas jet group 7 on the left side of the two heating sections and the second gas jet group 9 on the left side of the two heating sections, and the third gas enters the first gas jet group 11 on the left side of the two heating sections respectively by the first gas jet group 11 on the left side of the one heating section, The second gas valve group 13 at the left side of the heating section enters the first gas nozzle group 25 at the left side of the heating section and the second gas nozzle group 27 at the left side of the heating section; the other way is divided into three ways, the fourth way of gas respectively enters the first gas jet group 30 on the right side of the soaking section and the second gas jet group 32 on the right side of the soaking section through the first gas valve group 45 on the right side of the soaking section and the second gas valve group 47 on the right side of the soaking section, the fifth way of gas respectively enters the first gas jet group 35 on the right side of the two heating sections and the second gas jet group 37 on the right side of the two heating sections through the first gas valve group 49 on the right side of the two heating sections and the second gas valve group 51 on the right side of the two heating sections, and the sixth way of gas respectively enters the first gas jet group 40 on the right side of the one heating section and the second gas jet group 42 on the right side of the one heating section through the first gas valve group 53 on the right side of the heating section and the second gas valve group 55 on the right side of the heating section; the air preheated by the air heat exchanger 65 is divided into two paths by the air main 57, wherein one path is divided into three paths, the first air enters the first air nozzle group 14 on the left side of the soaking section and the second air nozzle group 16 on the left side of the soaking section by the first air valve group 2 on the left side of the soaking section and the second air valve group 4 on the left side of the soaking section, the second air enters the first air nozzle group 19 on the left side of the second heating section and the second air nozzle group 21 on the left side of the second heating section by the first air valve group 6 on the left side of the second heating section and the second air valve group 8 on the left side of the second heating section, and the third air enters the first air nozzle group 24 on the left side of the first heating section and the second air nozzle group 26 on the left side of the second heating section by the first air valve group 10 on the left side of the heating section and the second air valve group 12 on the left side of the heating section; the other way is divided into three ways, the fourth air enters the first air jet group 29 on the right side of the soaking section and the second air jet group 31 on the right side of the soaking section through the first air jet group 44 on the right side of the soaking section and the second air jet group 46 on the right side of the soaking section, the fifth air enters the first air jet group 34 on the right side of the two heating sections and the second air jet group 36 on the right side of the two heating sections through the first air jet group 48 on the right side of the two heating sections and the second air jet group 50 on the right side of the two heating sections, and the sixth air enters the first air jet group 39 on the right side of the one heating section and the second air jet group 41 on the right side of the one heating section through the first air jet group 52 on the right side of the heating section and the second air jet group 54 on the right side of the heating section; the tail gas passes through the second flue valve 64, the air heat exchanger 65, the third flue valve 66, the gas heat exchanger 62 and the first flue valve 61 in sequence, and is finally discharged from the chimney 60.
Simultaneously, coal gas and air enter the pulse heating device 1 through pulse burner groups for mixed combustion, wherein a first air nozzle group 14 on the left side of a soaking zone and a first coal nozzle group 15 on the left side of the soaking zone form a first pulse burner group on the left side of the soaking zone, a second air nozzle group 16 on the left side of the soaking zone and a second coal nozzle group 17 on the left side of the soaking zone form a second pulse burner group on the left side of the soaking zone, a first air nozzle group 19 on the left side of the two heating zones and a first coal nozzle group 20 on the left side of the two heating zones form a first pulse burner group on the left side of the two heating zones, a second air nozzle group 21 on the left side of the two heating zones and a second coal nozzle group 22 on the left side of the two heating zones form a second pulse burner group on the left side of the two heating zones, a first air nozzle group 24 on the left side of the one heating zone and a first nozzle group 25 on the left side of the heating zone form a first pulse burner group on the left side of the heating zone, and a second air nozzle group 26 on the left side of the heating zone and a second coal nozzle group 27 on the left side of the heating zone form a second pulse burner group on the left side of the heating zone; the soaking zone right side first air jet group 29 and the soaking zone right side first gas jet group 30 constitute a soaking zone right side first pulse burner group, the soaking zone right side second air jet group 31 and the soaking zone right side second gas jet group 32 constitute a soaking zone right side second pulse burner group, the two heating zone right side first air jet group 34 and the two heating zone right side first gas jet group 35 constitute a two heating zone right side first pulse burner group, the two heating zone right side second air jet group 36 and the two heating zone right side second gas jet group 37 constitute a two heating zone right side second pulse burner group, the first heating zone right side first air jet group 39 and the first heating zone right side first gas jet group 40 constitute a heating zone right side first pulse burner group, and the first heating zone right side second air jet group 41 and the first heating zone right side second gas jet group 42 constitute a heating zone right side second pulse burner group.
When the X80 steel billet is heated, working condition information of the steel billet and the heating furnace is shown in table 1:
TABLE 1 optimization cases of billet heating model
As shown in table 1, the throughput (i.e., billet loading) of the pulse heating apparatus 1 was 100t/h, and the dimensions were as follows: the load ratio of the first heating section, the second heating section and the soaking section of the pulse burner is 2:2:1, the gas is mixed gas, and the components are as follows: the ratio of CO 2 is 8.5%, the ratio of CO 14.5%, the ratio of N 2 is 23%, the ratio of H 2 is 42%, the ratio of other gases is 12%, the gas flow is 13800m 3/H, the gas preheating temperature is 200-300 ℃, the air flow is 32000m 3/H, the air preheating temperature is 450-550 ℃, the billet is X80 pipeline steel with the thickness of 2.98mx1.8mx0.25m, the initial temperature of the billet entering the furnace is 20 ℃, and the target final temperature is 1200 ℃.
According to the working condition information in table 1, the heating model optimizing method provided by the invention carries out combustion calculation, heat transfer calculation and finite difference iteration of a billet temperature field, the calculation and optimizing process is shown in fig. 5, the final temperature in the heating calculation model obtained after one-time correction is 1195-1200 ℃, and the difference between the final temperature and the actual measured final temperature is only less than 5 ℃, so that the heating model can be put into use.
The original heating model calculation method is adopted for calculation, the obtained final temperature in the original heating calculation model is 1150 ℃, the difference between the final temperature and the actual measured final temperature is 50 ℃, and the actual application can be realized after multiple corrections are required.
Through one or more embodiments of the present invention, the present invention has the following benefits or advantages:
The invention discloses an optimization method of a billet heating model, which is characterized in that a segmentation input parameter required by heating model calculation more in line with the actual working condition of a billet and the actual working condition of a heating furnace is obtained by adopting a de-novo calculation mode of combustion calculation and heat transfer calculation, then a calculation heating model is obtained by adopting a finite difference iteration method, and the billet heating is controlled by using the calculation heating model to obtain the actual heating data of the billet; and correcting the heating model according to the temperature deviation between the actual heating data and the calculated heating model. The combustion, heat transfer and billet temperature field simulation are integrated with the heating model correction process through the de-header calculation of billet heating, so that the calculation accuracy of the billet heating model is improved, the iteration speed of the billet heating model is accelerated, the correction times of the heating model are reduced, the effective control of the billet heating temperature and quality is realized, and the heating control cost is reduced.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A method for optimizing a billet heating model, the method comprising:
Acquiring initial parameters of combustion calculation, performing the combustion calculation, and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
Acquiring initial parameters of heat transfer calculation, performing heat transfer calculation according to the sectional furnace temperature, and determining the steel billet final temperature Tz, the steel billet sectional specific heat C pj, the steel billet sectional heat conductivity coefficient lambda j and the steel billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging amount and heating furnace size information;
According to the billet charging temperature T 0, the billet ending temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conduction coefficient lambda j and the billet heating time T, performing billet heating temperature field simulation by adopting a finite difference iteration method to obtain a billet heating calculation model;
Heating the steel billet according to the steel billet heating calculation model to obtain actual temperature rising data of the steel billet in the heating process;
Correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual heating data to obtain a target calculation heating model;
the method for simulating the billet heating temperature field by adopting the finite difference iteration method, to obtain a billet heating calculation model, specifically comprises the following steps:
Determining a thickness step delta x according to the thickness h of the steel billet, determining a time step delta tau according to the heating time t, and constructing a calculation grid of thickness nodes-time steps;
Taking the steel billet charging temperature T 0 as an initial value, and carrying out finite difference iteration on the calculation grid according to the steel billet sectional specific heat C pj and the steel billet sectional heat conductivity coefficient lambda j to obtain node calculation temperatures of all thickness nodes on the calculation grid along with the change of the time step delta tau Calculating the temperature/> from the nodesObtaining the billet heating calculation model; wherein i is more than or equal to 1 and less than or equal to h/delta x and is a positive integer, and n is more than or equal to 1 and less than or equal to t/delta tau and is a positive integer.
2. The optimization method according to claim 1, wherein the determining of the combustion load, the flue gas temperature and the flue gas flow rate of the heating furnace comprises:
determining the combustion load according to the gas volume flow and the gas low-position heating value;
determining the flue gas temperature according to the gas volume flow, the gas low-level heating value, the gas preheating temperature, the gas specific heat, the air-fuel ratio, the air specific heat, the air preheating temperature and the air volume flow;
and determining the flue gas flow according to the theoretical flue gas amount, the theoretical dry air amount and the air coefficient.
3. The optimization method of claim 1, wherein the gas components include CO, CO 2、N2, and H 2; the preheating temperature of the coal gas is 200-300 ℃, and the preheating temperature of the air is 450-550 ℃.
4. The optimization method according to claim 1, wherein determining the billet termination temperature Tz, the billet specific heat of segment C pj, the billet segment thermal conductivity λ j and the billet heating time t specifically comprises:
determining the billet heat absorption quantity Q according to the sectional furnace temperature and the billet loading quantity;
Determining a billet finishing temperature Tz according to the billet heat absorption Q, the billet charging temperature T 0 and the billet charging specific heat C p0;
Determining the billet sectional specific heat C pj according to the billet finishing temperature Tz and the billet charging specific heat C p0;
Determining the billet sectional heat conduction coefficient lambda j according to the billet finishing temperature Tz and the billet charging heat conduction coefficient lambda 0;
And determining the billet heating time t according to the billet finishing temperature Tz, the billet sectional specific heat C pj and the billet sectional heat conduction coefficient lambda j.
5. The optimization method of claim 1, wherein the staged furnace temperature comprises:
The furnace temperature of the first heating section is 800-1100 ℃, the furnace temperature of the second heating section is 1100-1150 ℃, and the furnace temperature of the soaking section is 1150-1250 ℃.
6. The optimization method according to claim 1, wherein the finite difference iteration is performed on the calculation grid according to the billet sectional specific heat C pj and the billet sectional heat conductivity coefficient λ j with the billet charging temperature T 0 as an initial value, specifically including:
Establishing a linear equation set according to the following finite difference equation, taking the billet charging temperature T 0 as the initial value of each thickness node, and calculating the temperature for the node Performing finite difference iteration:
Wherein ρ g is the billet density.
7. The optimizing method according to claim 6, wherein the correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual temperature rise data to obtain the target calculation heating model specifically comprises:
Judging whether the absolute value of the temperature deviation between the steel billet calculation final temperature in the steel billet heating calculation model and the steel billet actual final temperature in the actual temperature rise data is within 5 ℃;
If yes, determining the billet heating calculation model as a target calculation heating model;
if not, calculate the temperature from the node Node calculation temperature/>, corresponding to node k of target thickness
Determining node temperature rise data corresponding to the target thickness node k and the time step Deltaτ from the actual temperature rise data
Calculating a temperature for the nodeAnd the node warming data/>Performing mean value processing to obtain the target node temperature/>, of the target thickness node kThe target node temperature/>And (5) performing polynomial fitting to obtain a target heating model.
8. An optimizing apparatus for a billet heating model, characterized in that the optimizing apparatus comprises:
The combustion calculation module is used for acquiring initial parameters of combustion calculation, performing the combustion calculation and determining the combustion load, the flue gas temperature and the flue gas flow of the heating furnace; determining the sectional furnace temperature of the heating furnace according to the combustion load, the flue gas temperature and the flue gas flow; the combustion calculation initial parameters include: the method comprises the steps of gas preheating temperature, gas components, gas volume flow, air preheating temperature, air volume flow, pulse burner load and pulse burner quantity;
The heat transfer calculation module is used for acquiring heat transfer calculation initial parameters, carrying out heat transfer calculation according to the sectional furnace temperature, and determining billet finishing temperature Tz, billet sectional specific heat C pj, billet sectional heat conductivity coefficient lambda j and billet heating time t; the heat transfer calculation initial parameters include: billet size, billet composition, billet charging temperature T 0, billet charging amount and heating furnace size information;
The temperature field simulation module is used for performing billet heating temperature field simulation by adopting a finite difference iteration method according to the billet charging temperature T 0, the billet ending temperature Tz, the billet sectional specific heat C pj, the billet sectional heat conduction coefficient lambda j and the billet heating time T to obtain a billet heating calculation model;
the acquisition module is used for heating the steel billet according to the steel billet heating calculation model and acquiring actual temperature rise data of the steel billet in the heating process;
the correction module is used for correcting the billet heating calculation model according to the temperature deviation between the billet heating calculation model and the actual heating data to obtain a target calculation heating model;
the temperature field simulation module is specifically configured to:
Determining a thickness step delta x according to the thickness h of the steel billet, determining a time step delta tau according to the heating time t, and constructing a calculation grid of thickness nodes-time steps;
Taking the steel billet charging temperature T 0 as an initial value, and carrying out finite difference iteration on the calculation grid according to the steel billet sectional specific heat C pj and the steel billet sectional heat conductivity coefficient lambda j to obtain node calculation temperatures of all thickness nodes on the calculation grid along with the change of the time step delta tau Calculating a temperature from the node
Obtaining the billet heating calculation model; wherein i is more than or equal to 1 and less than or equal to h/delta x and is a positive integer, and n is more than or equal to 1 and less than or equal to t/delta tau and is a positive integer.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the optimization method of any one of claims 1-7 when the program is executed by the processor.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103544356A (en) * | 2013-10-30 | 2014-01-29 | 中冶南方（武汉）信息技术工程有限公司 | Heat treatment furnace heating model calculation method based on graphic processing unit (GPU) |
| CN104049649A (en) * | 2013-03-14 | 2014-09-17 | 宝山钢铁股份有限公司 | Model control method of heating furnace temperature |
| CN104331540A (en) * | 2014-10-13 | 2015-02-04 | 大连理工大学 | Method for optimizing convectional heat exchange confident of cooling water in continuous casting secondary cooling zone |
| CN105349768A (en) * | 2015-11-26 | 2016-02-24 | 首钢京唐钢铁联合有限责任公司 | Heating control method for radiant tube of continuous annealing furnace |
| CN106636606A (en) * | 2016-12-30 | 2017-05-10 | 北京和隆软件有限公司 | Heating furnace temperature control method based on simulation model |
| CN110918655A (en) * | 2019-11-30 | 2020-03-27 | 宝钢特钢韶关有限公司 | Refined heating control method |
-
2020
- 2020-07-13 CN CN202010667290.0A patent/CN111950176B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104049649A (en) * | 2013-03-14 | 2014-09-17 | 宝山钢铁股份有限公司 | Model control method of heating furnace temperature |
| CN103544356A (en) * | 2013-10-30 | 2014-01-29 | 中冶南方（武汉）信息技术工程有限公司 | Heat treatment furnace heating model calculation method based on graphic processing unit (GPU) |
| CN104331540A (en) * | 2014-10-13 | 2015-02-04 | 大连理工大学 | Method for optimizing convectional heat exchange confident of cooling water in continuous casting secondary cooling zone |
| CN105349768A (en) * | 2015-11-26 | 2016-02-24 | 首钢京唐钢铁联合有限责任公司 | Heating control method for radiant tube of continuous annealing furnace |
| CN106636606A (en) * | 2016-12-30 | 2017-05-10 | 北京和隆软件有限公司 | Heating furnace temperature control method based on simulation model |
| CN110918655A (en) * | 2019-11-30 | 2020-03-27 | 宝钢特钢韶关有限公司 | Refined heating control method |
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